Translating Matlab's filter settings to Python's scipy.signal.buttord

Question

I am trying to replicate a Matlab filter design in Python based on the instructions here [1]. However, there are certain parameters of fdesign.bandpass for which I am unsure how to translate them to the scipy.signal.buttord, such as second and first stopband attenuation: "Ast1,Ap,Ast2" [2]. Scipy's buttord allows only to specify the maximum loss in the passband and the minimum attenuation in the stopband: "gpass, gstop" [3]. Further, I am unsure how to properly translate group delays?

Help very much appreciated! Best, Tristan

The Matlab filter is specified as [4, 5]:

%eegFS = 2000;  % Signal freq, Hz
%lcut = 5;  % low cut freq, Hz
%hcut = 100;  % high cut freq, Hz
%attenHz = 4;  % transition band
%attendB = 40; % attenuation

nyq = round(eegFS/2);

%make bandpass
Fstop1 = (lcut - attenHz)  / nyq;  % First Stopband Frequency
Fpass1 = lcut  / nyq;  % First Passband Frequency
Fpass2 = hcut / nyq;  % Second Passband Frequency
Fstop2 = (hcut + attenHz) / nyq;  % Second Stopband Frequency
Astop1 = attendB;    % First Stopband Attenuation (dB)
Apass  = 1;     % Passband Ripple (dB)
Astop2 = attendB;    % Second Stopband Attenuation (dB)
h = fdesign.bandpass('fst1,fp1,fp2,fst2,ast1,ap,ast2', Fstop1, Fpass1, ...
                 Fpass2, Fstop2, Astop1, Apass, Astop2);
Hd = design(h, 'kaiserwin');   
b = Hd.Numerator;

%group delay
[a,f] = grpdelay(b,1,nyq,eegFS);
k = f >= lcut & f <= hcut;
gd = fix(mean(a(k)));

% apply filter
eegF = filter(b, 1, eegData, [], 2);
eegF = cat(2,eegF(:,gd+1:end),zeros(size(eegF,1),gd));

[1] https://stackoverflow.com/questions/12093594/how-to-implement-band-pass-butterworth-filter-with-scipy-signal-butter [2] https://se.mathworks.com/help/dsp/ref/fdesign.bandpass.html [3] https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.buttord.html [4] https://gin.g-node.org/ddvorak/DentateSpikes/src/master/code/getFIRbandpass.m [5] https://gin.g-node.org/ddvorak/DentateSpikes/src/master/code/getDS.m